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ACM members and non-member alike are welcome to attend our popular series of free Learning Webinars by expert industry professionals, distinguished ACM award laureates, and visionary researchers from industry and academia. Focused on keeping our global audience of busy practitioners at the forefront of technical trends, professional development, and emerging technologies, the webinars are also popular with students and educators. Recent talks have covered topics in Artificial Intelligence and Machine Learning, Big Data and Data Science, Blockchain, Computer Vision, Deep Learning, JavaScript, Microservices, Python, Quantum Computing, and more. Registration is free and the webinars can be attended both live and on-demand, on desktop and mobile devices. Check this page frequently for upcoming events as well as our on-demand archive. To subscribe to our webinar announcements, email learning@acm.org.

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This tutorial extensively covers the definitions, nuances, challenges, and requirements for the design of interpretable and explainable machine learning models and systems in healthcare. We discuss many uses in which interpretable machine learning models are needed in healthcare and how they should be deployed. Additionally, we explore the landscape of recent advances to address the challenges model interpretability in healthcare and also describe how one would go about choosing the right interpretable machine learning algorithm for a given problem in healthcare.

ACM award winners, leading researchers, industry veterans, thought leaders, and innovators address today and tomorrow's hottest topics and issues in computing for busy practitioners, as well as educators, students, and researchers. Check out our archive of these ACM Learning Webinars, free for members and non-members alike.

Talks from some of the leading visionaries and bleeding-edge researchers in AI/ML: Fei-Fei Li on visual intelligence in computers and ImageNet; Eric Horvitz on AI solutions in the open world; and Tom Mitchell on using ML to study how the brain creates and represents language.